Zied Jemai

Including Sustainability Criteria into Inventory Models

Research on sustainability performance has considerably enriched operations management literature in recent years. However, work with quantitative models is still scarce. This paper contributes by revisiting classical inventory methods taking sustainability concerns into account. We believe that reducing all aspects of sustainable development to a single objective is not desirable. We thus reformulate the classical economic order quantity model as a multiobjective problem. We refer to this model as the sustainable order quantity model. Then, a multi-echelon extension of the sustainable order quantity model is studied. For both models, the set of efficient solutions (Pareto optimal solutions) is analytically characterized. These results are used to provide some insights about the effectiveness of different regulatory policies to control carbon emissions. We also use an interactive procedure that allows the decision maker to quickly identify the best option among these solutions. The proposed interactive procedure is a new combination of multi-criteria decision analysis techniques.

Survey: A review on simulation models applied to emergency medical service operations

Emergency medical services (EMS) are public safety systems responsible for the pre-hospital stabilization and transport of seriously injured patients. The goal of such systems is to respond adequately to population calls by providing first aid services and transferring patients, when needed, to the emergency department of the appropriate hospital. In order to achieve this goal, a variety of tools (e.g. simulation, mathematical programming and queuing theory models) have been used to improve the performance of EMS. This paper focuses specifically on computer simulation models used for the analysis and improvement of EMS. In particular, we give a critical overview of the existing international literature on simulation models for EMS by pinpointing the issues considered, the associated modeling assumptions as well as the results obtained. Such a contribution is lacking in the current literature.

Improving the performance of retail stores subject to execution errors: coordination versus RFID technology

This paper analyzes a Newsvendor type inventory model in which a manufacturer sells a single product to a retailer store whose inventory is subject to errors stemming from execution problems. Hence, within the store, all of the products are not available on shelf for sales either because the replenishment of the shelf from the backroom is subject to execution errors that mainly result in products lost in the backroom or products misplaced on the other shelves of the store. We compare two situations: in the first situation, the two supply chain actors are aware of errors and optimize their ordering decisions by taking into account this issue. The second situation deals with the case where an advanced automatic identification system such as the Radio Frequency Identification technology is deployed in order to eliminate errors. Each situation is developed for three scenarios: in the centralized scenario, we consider a single decision-maker who is concerned with maximizing the entire supply chain’s profit; in the decentralized uncoordinated scenario, the retailer and the manufacturer act as different parties and do not cooperate. The third scenario is the decentralized coordinated scenario where we give conditions for coordinating the channel by designing a buyback contract.

Analysis of order-up-to-level inventory systems with compound Poisson demand

We analyse a single echelon single item inventory system where the demand and the lead time are stochastic. Demand is modelled as a compound Poisson process and the stock is controlled according to a continuous time order-up-to (OUT) level policy. We propose a method for determining the optimal OUT level for cost oriented inventory systems where unfilled demands are backordered. We first establish an analytical characterization of the optimal OUT level. The actual calculation is based on a numerical procedure the accuracy of which can be set as highly as desired. By means of a numerical investigation, we show that the method is very efficient in calculating the optimal OUT level. We compare our results with those obtained using an approximation proposed in the literature and we show that there is a significant difference in accuracy for slow moving items. Our work allows insights to be gained on stock control related issues for both fast and slow moving Stock Keeping Units (SKUs).

A simulation study to improve the performance of an emergency medical service: Application to the French Val-de-Marne department

Abstract The French Emergency Medical services, which are known as SAMU (the acronym of Urgent Medical Aid Services in French), are public safety systems responsible for the coordination of pre-hospital care under emergency conditions throughout a particular geographic region. The goal of these systems is to respond in a timely and adequate manner to population calls, to provide first- aid services and to transfer patients to the appropriate care facility when needed. The current study aims to develop the process of the Val-de-Marne department’s SAMU system (SAMU 94) in an efficient manner that meets the population’s needs using limited resources. For this purpose, we propose a discrete event simulation (DES) model implemented in the ARENA software to analyze possible changes in the SAMU 94 processes that would lead to enhanced operational efficiency for coverage performance (i.e., the percentage of calls for which the patient wait time before a SAMU 94 rescue team arrives does not exceed a specific target time). Hence, the model enables to test five categories of scenarios that are mainly related to the level of resources used as well as the location of rescue teams throughout the service area. Among other results, we found that repositioning a portion of the existing teams into potential bases increased the 20-min coverage performance up to 4.5% in average. Furthermore, this improvement in coverage can reach 7.3% when the whole fleet is relocated based on the multi-period redeployment plan obtained from simulation optimization.

Decentralized inventory control in a two-stage capacitated supply chain

This paper investigates a two-stage supply chain consisting of a capacitated supplier and a retailer that faces a stationary random demand. Both the supplier and the retailer employ base stock policies for inventory replenishment. All unsatisfied demand is backlogged and the customer backorder cost is shared between the supplier and the retailer. We investigate the determination of decentralized inventory decisions when the two parties optimize their individual inventory-related costs in a noncooperative manner. We explicitly characterize the Nash equilibrium inventory strategies and identify the causes of inefficiency in the decentralized operation. We then study a set of simple linear contracts to see whether these inefficiencies can be overcome. Finally, we investigate Stackelberg games where one of the parties is assumed to be dominating.

Inventory routing problems in a context of vendor-managed inventory system with consignment stock and transshipment

The inventory routing problem involves the integration and the coordination of two components of the logistics value chain: the inventory management and the vehicle routing decisions. In fact, the aim is to jointly decide on the distribution tour, from a distribution centre to a set of locations, and on the inventory policy for each location. Although many research investigations show great interest in policies such as transshipment or dynamic routings on the distribution system performances, these approaches are often criticised in practice as being too restrictive. In this article, we consider the inventory routing framework in a supplier integration context, i.e. a vendor-managed inventory with a consignment stock policy. Under such framework, we show that the transshipment brings more benefits than the classical context. In particular, we consider the case of static routings and we numerically show that transshipment permits to better optimise the distribution tours and to improve the global performance of the supply network.

Analysis of a periodic review inventory control system with perishables having random lifetime

We consider an order up to level policy for perishable items with random lifetime. We investigate two cases: the first one is the case where excess demand is completely lost and the second one deals with full backorders. Demands arrive according to a Poisson process. The lifetime of each item is assumed to be exponentially distributed and the procurement lead time is constant. We also assume that there is at most one outstanding order at any time. We model this inventory system as a Markov process in which stationary regime can be characterised. This model allows us to get insights on the impact of the model parameters on the overall system performance in terms of costs.

Impact of coordination on costs and carbon emissions for a two-echelon serial economic order quantity problem

Coordination in supply chains consists in aligning the decisions made by several echelons to reach a globally optimal solution called the centralized solution, and to share the benefits among the actors. This concept has been studied widely from a cost optimization perspective but coordination is also proposed by practitioners and academics as a solution to reduce carbon emissions. This article compares the costs and carbon emissions resulting from a non-coordinated two-echelon serial economic order quantity model to that of the centralized solution. Our model accounts for transportation and inventory related costs and emissions and we consider vehicle capacities. We derive new results to solve the problem in the non-coordinated and in the centralized cases. We provide sufficient conditions ensuring that coordination enables reducing both costs and emissions and we show that these conditions are satisfied in many applications. On the other hand, we also identify situations for which coordination leads to an increase in emissions and we provide sufficient conditions. In such situations, we additionally show how to obtain a solution decreasing both costs and carbon emissions. We use multiobjective optimization to identify all these solutions and we provide a series of insights.

A comprehensive simulation modeling of an emergency department: a case study for simulation optimization of staffing levels

We propose a Discrete Event Simulation (DES) model for an emergency department (ED). The model is developed in close collaboration with the French hospital Saint Camille, and is validated using real data. The objective of this model is to help ED managers better understand the behavior of the system and to improve the ED operations performance. The most essential features of an ED are considered in the model. A case study is conducted in order to allow decision makers select the most relevant investment in the human staffing budget. A simulation-based optimization algorithm is adopted to minimize the average Length of Stay (LOS) under a budget constraint. We conduct a sensitivity analysis on the optimal average LOS as a function of the staffing budget, and derive useful recommendations to managers on how the budget can impact the performance of the system.